Reliability estimation based on ranked set sampling

In this paper we consider the problem of estimating the reliability of an exponential component based on a Ranked Set Sample (RSS) of size n. Given the first r observations of that sample, 1≤r≤n, we construct an unbiased estimator for this reliability and we show that these n unbiased estimators are the only ones in a certain class of estimators. The variances of some of these estimators are compared. By viewing the observations of the RSS of size n as the lifetimes of n independent k-out-of-n systems, 1≤k≤n, we are able to utilize known properties of these systems in conjunction with the powerful tools of majorization and Schur functions to derive our results.     

Formulas for stationary planar fibre processes III – intersections with fibre systems

In this paper we investigate the distribution of the periodogram, respectively, the periodogram matrix for stationary random sequences. These .distributions are consid¬ered in the case of a fixed frequency as well as in the case of a finite number of frequencies for Gaussian sequences and for sequences of independent random variables. The exact distribution is obtained in the case of a fixed frequence for one-dimensional GAUSsian sequences. Asymptotic expansions, respectively, the rate of convergence to the asymptotic distribution are given in the case mentioned above     

L Ranked Set Sampling: A Generalization Procedure for Robust Visual Sampling

In this article, a robust ranked set sampling (LRSS) scheme for estimating population mean is introduced. The proposed method is a generalization for many types of ranked set sampling that introduced in the literature for estimating the population mean. It is shown that the LRSS method gives unbiased estimator for the population mean with minimum variance providing that the underlying distribution is symmetric. However, for skewed distributions a weighted mean is given, where the optimal weights is computed by using Shannon's entropy. The performance of the population mean estimator is discussed along with its properties. Monte Carlo comparisons for detecting outliers are made with the traditional simple random sample and the ranked set sampling for some distributions. The results indicate that the LRSS estimator is superior alternative to the existing methods.     

Fast and rigorous: Configurational determinants of strategic decision-making balance

A longstanding debate in the strategic decision-making literature has focused on whether top management teams (TMTs) can effectively balance speed and comprehensiveness when making important decisions. In our research, we build on early insights and pivot from considering whether TMTs can engage indecision-making that balances these tensions to focus instead on when certain types of TMTs are able to achieve such balance. We employ a novel configurational analytical approach and a theoretical framework built from role theory to examine the CEO-TMT interface in a new way. In so doing, we are able to identify specific CEO-TMT constellations that support decision-making that is both fast and rigorous. Using a unique primary dataset and an abductive, configurational approach grounded in fuzzy set qualitative comparative analysis (fsQCA), we identify six specific leader-team configurations that each facilitate decision processes characterized by rigorous intra-team debate, meaningful reconciliation of divergent ideas, and fast decision speed (which we describe as strategic decision-making balance). The range of CEO-TMT configurations that emerge from our analyses contribute new theory and findings for the strategic decision-making and interface literatures more broadly, as well as the specific research streams on executive gender, humility, and TMT structure.     

New two-stage sampling designs based on neoteric ranked set sampling

Neoteric ranked set sampling (NRSS) is a recently developed sampling plan, derived from the well-known ranked set sampling (RSS) scheme. It has already been proved that NRSS provides more efficient estimators for population mean and variance compared to RSS and other sampling designs based on ranked sets. In this work, we propose and evaluate the performance of some two-stage sampling designs based on NRSS. Five different sampling schemes are proposed. Through an extensive Monte Carlo simulation study, we verified that all proposed sampling designs outperform RSS, NRSS, and the original double RSS design, producing estimators for the population mean with a lower mean square error. Furthermore, as with NRSS, two-stage NRSS estimators present some bias for asymmetric distributions. We complement the study with a discussion on the relative performance of the proposed estimators. Moreover, an additional simulation based on data of the diameter and height of pine trees is presented.     

Estimation of system reliability for exponential distributions based on L ranked set sampling

Abstract

In the case where strength and stress both follow exponential distributions, this paper considers the maximum likelihood estimator (MLE) of the system reliability based on L ranked set sampling (LRSS). The proposed MLE is shown to have existence, uniqueness and asymptotic normality, and its asymptotic variance is obtained by the Fisher information matrix of LRSS. The values of asymptotic relative efficiencies show that the proposed MLE is always more efficient than the MLE using simple random sampling (SRS). However, the MLE using LRSS cannot be written in closed form. Therefore, the modified MLE is proposed using the technique replaced some terms in the maximum likelihood equations by their expectations. The newly modified MLE using LRSS is shown to be superior to the MLE using SRS. Finally, the proposed method is applied to a real data set on metastatic renal carcinoma study.     

逻辑函数绝对最小覆盖的改进算法

逻辑函数的绝对最小化算法存在的主要问题是运行时间过长和需要的存储空间过大,本文提出了一个从给定本源蕴源项集合中抽出一个绝对最小覆盖的算法,而时间空间的需求被大大地缩小了。     

黄金通衢拓市场 蔬果批发可增益

文章分析了在北仑区白峰镇兴建蔬菜果品批发市场的可能性及对该区、该镇经济发展的促进作用,最后提出了如何兴建该市场的具体建议。     

产品类型和感知风险对消费者属性同异选择的影响研究

前期的情境效应研究发现,相同属性同异选择集下的消费者选择行为完全相反,这为同异属性选择集下的消费者选择研究留下了悬而未决的矛盾.文章利用情境模拟实验法,将感知风险和产品类型纳入整合的研究框架,从感知、风险规避和效用等方面研究消费者属性同异选择行为.研究发现,高感知风险下消费者对趋同产品的选择显著多于低感知风险情形,而低感知风险情形下对趋异产品的选择则相反.同时,感知风险和产品类型对消费者属性同异选择存在交互作用,在高感知风险下对实用品的选择情形中,消费者倾向于趋同选择;在低感知风险下对享乐品的选择情形中,消费者偏好作出趋异选择;在其他情形下对消费者选择的影响则不显著.研究结论弥合了属性趋同效应和知觉聚焦效应的矛盾,对企业的同异策略选择提供了重要的参考依据.